In essence, he argues that Hierarchy is inevitable in human societal structures once they get above a certain size.

To quote Turchin:

For over 90 percent of our evolutionary history humans lived in small-scale groups”. Agreeing on a common course of action to achieve collective goals was relatively easy. It is quite possible to come to a consensus in a small group of ten or fewer people simply by having a common discussion, listening to everybody’s concerns, and not allowing anybody to dominate the decision-making process.
It is much harder, but still possible to concert a common policy in groups consisting of many tens of individuals; very difficult in groups of hundreds; and simply impossible once you get into thousands. That’s probably one of the fundamental principles of social dynamics.

The issue is the sheer difficulty of “getting things done” in large groups without some form of super-structure. He uses network analysis to show that, in theory a “network of networks” is possible:

The only way that large human groups can arrive at a common course of action is by structuring interpersonal connections. Imagine a large human group as a network in which any particular node (a person) has a thick connection to just a few other people, between 4 and 10 of such connections. This is a small enough number so that each person in a pair can know the other quite well, and they can rapidly coordinate their objectives and actions.
So the coordinator at the center of the network speaks to and gets feedback from ten other people. Those ten speak to ten more people each, and so on. It is possible to connect a group of any size using this scheme, by adding extra levels of communication and decision making. For example, a society with one million members would need six levels. We need only 10 levels to connect everybody on Earth!

The issue, of course, is that the people at the centre of this network have some form of hierarchical power, and that is where the problems start. Network effects mean there is an inevitable driver for the slightly bigger to get even bigger, whether its websites or people – and people are not neutral actors:

The problem, of course, is that as soon as you put someone in a central position of a decision-making network, you give them a lot of structural power, and they can, and often will, attempt to convert it into more malignant forms of power: ability to order others around, and acquisition of a disproportionate amount of resources. If there are no effective checks on leaders, then hierarchy breeds inequality. Sociologists even have a name for this, the Iron Law of Oligarchy.

And it’s that Iron law that makes it so difficult to run non hierarchical networks, as Turchin points out. Humanity’s history is to scale from small, fairly heterarchical clans to very hierarchical structures where at its extreme the lowest level people were (and in some cases still are) slaves. He shows that more just, less hierarchical societal structures eventually win out as they are more effective, but it is a long and winding road – and the winning structures are still hierarchies, just not as extreme. To summarise, his analysis has 2 conclusions pertinent to any thoughts about New ways of Working:

Firstly,

it’s a pipe dream to imagine that a large-scale society (e.g., a million people or more – a small nation by today’s standards!) can be organized in a non-hierarchical, horizontal way. Hierarchy (in its neutral sense) is the only way to organize large-scale societies

Secondly, therefore:

…what we need is not less hierarchy, but more control over our leaders to ensure that they govern for the collective good, rather than for selfish needs of themselves and their cronies.

What’s this got to do with enterprises? Well, he talks of large scale societies of a million people or more, but we have yet to find a heterarchical case study of more than several tens of people. Those of you who read this blog will know we came to similar conclusions re human group sizes and the difficulty of managing large groups in heterarchical ways.

Looking at Dunbar’s numbers its clear that as humans our network management capacity in any form trips out at a sub 1,000 people level, so my hypothesis is that his statement is true not just for millions, but for several thousands well, and thus we suggest that any enterprise of c 1,000 or more (and probably smaller, down to the c 150 person Dunbar “tipping point” level when no one person can run a company on personal relationships only) will also inevitably become structurally hierarchical.

Thus, all the technichniques for heterarchical organisation structures are probably good up to a certain point, we posit c 150 people above (it’s also about where the infamous “startup breakdowns” seem to occur as Founders lose control of their companies if they don’t bring in formal layers) before a fairly formally structured hierarchy becomes inevitable.

Zappos’ experience with Holacracy seems to bear this out. In the article “Beyond the Holacracy hype” on HBR, they note a number of interesting features of flatter structures in operation:

Teams are the structure – In holacracy, they’re “circles”; in podularity, “pods”; at Valve, “cabals”; and at many companies, simply “teams.” Whatever they’re called, these basic components—not individuals, and not units, departments, or divisions—are the essential building blocks of their organizations.

Self-managing enterprises [HBR term for more heterarchical strucrures] have a lot more of them —the overall organizational structure is diced much more finely. After Zappos implemented holacracy, 150 departmental units evolved into 500 circles.

Leadership is distributed among roles, not individuals (people usually hold multiple roles, on various teams). Leadership responsibilities continually shift as the work changes and as teams create and define new roles. (Our note – This particular structure seems to be a holacracy thing, rather than a general feature, but by definition a non-hierarchical structure has to vest various leadership functions across multiple people so most will probably have similar divisions)

Technology is essential for keeping these changes straight. In a holacracy, for example, enterprise software such as GlassFrog or holaSpirit is typically used to codify the purpose, accountability, and decision rights of every circle and role, and the information is accessible to anyone in the organization.

And this is where it starts to go wrong, as:

It complicates actually doing the work, because employees struggle with fragmentation. A significant body of literature on goal setting (aptly summarized by Marc Effron and Miriam Ort in their book One Page Talent Management) finds that employees perform less well on each goal as they take on more beyond just a handful. At Zappos, each of the 7.4 roles an individual fills contains an average of 3.47 distinct responsibilities, resulting in more than 25 responsibilities per employee.

Having so many roles complicates compensation. As people assemble their personal portfolios of roles, it becomes difficult to find clear benchmarks or market rates. For instance, what would you pay someone who divides her time between developing software, serving as the lead link for a software development team, working on marketing strategy, creating internal leadership training, doing community outreach, and planning events?

Third, role proliferation complicates hiring, both into the organization and into particular roles. Although new employees are brought on to meet specific needs, they quickly start adding other roles to their portfolios. In the last three months of 2015, Zappos’s roughly 1,500 employees made and received 17,624 role assignments (11.7 per employee), or about 195 per day.

So in essence, the operation became less efficient and added cost and friction. They also found decisions became worse, HBR notes that to make smarter decisions in this sort of system, all members must exercise their power and voices, which doesn’t always happen. Their eventual conclusion – as we’d expected to see – was that it works more in a smaller, startup environment:

Using self-management principles to design an entire organization makes sense if the optimal level of adaptability is high—that is, if the organization operates in a fast-changing
environment in which the benefits of making quick adjustments far outweigh the costs, the wrong adjustments won’t be catastrophic, and the need for explicit controls isn’t significant. That’s why many start-ups are early adopters.

They also note that certain structures, like game design company Valve, it can scale as the whole business is still like a startup, But, once it becomes important to hit deadlines, deliver stuff etc it seems to struggle more….

….in reliability-driven industries such as retail banking and defense contracting, hierarchical structures prevail, even if there is room for niche competitors (in banking, think of Umpqua, famous for having a phone in every branch that enables customers to ring the CEO’s office) or for certain units within the organization (such as the original Skunk Works at Lockheed Martin) to go against the traditional grain.

Ultimately, and somewhat ironically, the next generation of self-managing teams is demanding a new generation of leaders — senior individuals with the vision to see where it is best to set aside hierarchy for another way of operating, but also with the courage to defend hierarchy where it serves the institution’s fundamental goals.

But even if this works (if…) the issue becomes – as Turchin suggests in his second point – more about how one then asserts control over the leaders. Sadly, looking at businesses, at the moment there is no co-ordinated approach to this problem, more than one study has shown that business leadership attracts the sort of people one shouldn’t let anywhere near a top position – it is a mismatch of cultural, communicational, regulatory and punitive (legal) approaches.

Alan is the co-founder and CXO of Agile Elephant. He has spent 30 years helping companies to use cutting edge technologies to improve business performance. He was involved in the design of early factory and logistics networks, and in using them to drive lean operations in digital supply chains from the very early days of their inception.